Extended Reality (XR) is an emerging technology that enables enhanced interaction between the real world and virtual environments. In this study, we conduct a scoping review of XR engines for developing gamified apps and serious games. Our study revolves around four aspects: (1) existing XR game engines, (2) their primary features, (3) supported serious game attributes, and (4) supported learning activities. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model to conduct the scoping review, which included 40 primary studies published between 2019 and 2023. Our findings help us understand how current XR engines support the development of XR-enriched serious games and gamified apps for specific learning activities. Additionally, based on our findings, we suggest a set of pre-established game attributes that could be commonly supported by all XR game engines across the different game categories proposed by Lameras. Hence, this scoping review can help developers (1) select important game attributes for their new games and (2) choose the game engine that provides the most support to these attributes.

Serious games play a significant role in the teaching and learning process by focusing on educational objectives rather than purely on entertainment. By addressing specific educational needs, these games provide targeted learning experiences. The integration of emotion recognition technology into serious games can further enhance teaching and learning by identifying areas where students may need additional support, The integration of emotion recognition into a serious game facilitates the learning of mathematics by allowing the identification of emotional impact on learning and the creation of a tailored learning experience for the student. This study proposes a challenge-based and task-based math serious game that integrates facial emotion recognition named TasksZE. TasksZE introduces a novel approach by adjusting gameplay based on detected emotions, which includes real-time emotion analysis and the cross-validation of emotions. We conducted a usability evaluation of the game using the System Usability Scale (SUS) as a reference, and the results indicate that the students feel that TasksZE is easy to use, the functions are well integrated, and most people can learn to use it very quickly. The students answered that they would use this system frequently since they felt motivated by game attributes, rewards, and level progression. These elements contributed to a more engaging and effective learning experience.